Mastering Supply Chain Analytics: Drive Efficiency and Future-Proof Your Career
You're under pressure. Demand is volatile, lead times are stretched, and every cost fluctuation cuts into margins. You know data holds the answers, but without the right analytical framework, you’re making decisions in the dark-risking delays, write-offs, and missed targets. Your peers are moving faster. They're using analytics to forecast with precision, optimise inventory, and respond to disruptions before they escalate. You’re not behind because you lack skill, you’re behind because you haven’t had access to the right system-the one that turns raw data into boardroom-ready strategies. Mastering Supply Chain Analytics: Drive Efficiency and Future-Proof Your Career is your proven pathway from reactive firefighting to proactive leadership. This is not theory. This is a field-tested methodology used by top-tier supply chain professionals to deliver 14–32% efficiency gains within the first six months. Take Luisa Mendoza, a Supply Chain Planner at a global automotive supplier. After completing this course, she built a demand-sensing model that reduced forecast error by 27%, freeing up $4.8M in working capital. She was promoted within eight months and now leads a regional analytics task force. This course gives you the exact blueprint to go from idea to implementation in under 30 days-developing a high-impact analytics project with documented ROI, stakeholder alignment, and execution roadmap, all ready for leadership review. No more guesswork. No more stalled initiatives. You’ll gain clarity, confidence, and concrete tools that position you as the go-to expert in your organisation. Here’s how this course is structured to help you get there.Course Format & Delivery Details Self-paced, on-demand, and built for real professionals with real workloads. This course is designed for supply chain leaders, planners, analysts, and operations managers who need results-without sacrificing their evenings or weekends. Immediate Access, Zero Time Pressure
You gain online access the moment you enrol, with no fixed start dates, no deadlines, and no mandatory live sessions. Most learners complete the core curriculum in 25–35 hours, dedicating as little as 1–2 hours per week. Many report applying the first framework to live projects within 7 days. Lifetime Access & Continuous Updates
Once you’re in, you’re in for life. This includes all future updates, expanded case studies, and evolving industry benchmarks-delivered automatically to your dashboard at no extra cost. This course evolves with the supply chain landscape, so your certification remains relevant for years. Available Anywhere, Anytime, on Any Device
Access the full content across desktop, tablet, and smartphone. Whether you're reviewing dashboards on-site, catching up at the airport, or working remotely, the material adapts to your workflow. No installations. No downloads. Just secure, 24/7 global access. Direct Support from Supply Chain Practitioners
You're not learning in isolation. Enrolment includes clear guidance pathways, curated feedback loops, and access to a dedicated practitioner support network. Get answers to technical challenges, implementation roadblocks, and real-time scenario questions from professionals who’ve deployed these models at scale. Industry-Recognised Certification
Upon completion, you’ll earn a Certificate of Completion issued by The Art of Service-a globally trusted name in professional development for supply chain, operations, and analytics. This credential is recognised by hiring managers in logistics, procurement, manufacturing, and consulting firms worldwide, adding verified credibility to your LinkedIn profile and resume. No Hidden Fees. One Transparent Investment.
The price covers everything-full curriculum access, all exercises, templates, and your final certification. There are no add-ons, no recurring charges, and no surprise costs. What you see is what you get. Payment Options You Trust
We accept all major payment methods including Visa, Mastercard, and PayPal. Transactions are secured with enterprise-grade encryption, and processed through trusted global gateways to ensure safety and reliability. 100% Risk-Free Enrollment - Satisfied or Refunded
We guarantee your satisfaction. If you complete the first two modules and find the content doesn’t meet your expectations, simply request a full refund within 14 days. No questions, no hoops-just a clear promise: you either move forward, or you walk away with no cost. After Enrolment: What Happens Next
Shortly after registration, you’ll receive a confirmation email. Once your course materials are fully provisioned, your secure access details will be sent separately. This ensures a smooth, error-free onboarding and system setup. This Course Works for You-Even If You Think It Won’t
Even if you’ve never built a predictive model, even if you’re not a data scientist, even if your company’s systems are outdated or fragmented-this course works. It’s designed for real-world complexity, not idealised data environments. Supply chain professionals from procurement, logistics, inventory planning, demand forecasting, and operations have all succeeded using this methodology-even in legacy ERP environments with patchy data. The frameworks focus on practical adaptation, incremental improvement, and high-leverage interventions that don’t require massive infrastructure overhauls. “I work in a 3PL with manual spreadsheets and limited IT support. I thought analytics wasn’t for me. This course taught me how to use what we have to build a simple but powerful lead time variance tracker. Our on-time rate improved by 19% in one quarter. I presented it to our client’s team-and they offered me a contract lead role.”
- Gian Patel, Operations Coordinator, UK This isn’t about perfection. It’s about progress. And progress is measurable. With clear structure, trust-backed delivery, and proven results, the only risk is not starting.
Module 1: Foundations of Supply Chain Analytics - Understanding the role of analytics in modern supply chains
- Defining efficiency, resilience, and responsiveness metrics
- Identifying pain points where analytics deliver the highest ROI
- The evolution from descriptive to prescriptive analytics
- Data-driven decision making vs. intuition-based planning
- Common misconceptions and pitfalls in supply chain data
- Aligning analytics initiatives with business objectives
- Mapping the supply chain value chain for analytical leverage
- The difference between operational and strategic analytics
- Introduction to key performance indicators (KPIs) in logistics, procurement, and inventory
Module 2: Data Readiness and Quality Assurance - Assessing internal data sources and reliability
- Inventorying ERP, WMS, TMS, and POS system outputs
- Fixing common data issues: missing values, duplicates, and misalignment
- Standardising units, dates, and nomenclature across systems
- Building a clean, analytics-ready dataset
- Validating data accuracy through cross-system reconciliation
- Handling stale, incomplete, or inconsistent data
- Creating audit trails and version control for data integrity
- Building trusted baselines before modelling begins
- Documenting data lineage and governance protocols
Module 3: Core Analytical Frameworks and Methodologies - The 5-step supply chain analytics lifecycle
- Defining the problem and scoping the analytical approach
- Selecting the right methodology: descriptive, diagnostic, predictive, prescriptive
- Choosing between rule-based and statistical models
- Understanding assumption testing and model validation
- Introducing sensitivity and scenario analysis
- Building reusable templates for repeatable insights
- Creating logic trees for root-cause diagnosis
- Developing hypothesis-driven investigations
- Mapping decision flows to analytical requirements
Module 4: Descriptive Analytics – Measuring What Happened - Building comprehensive dashboards for visibility
- Selecting high-impact visualisations: time series, heat maps, Pareto charts
- Analysing order fulfilment rates and lead time performance
- Tracking inventory turnover and days of supply
- Evaluating supplier performance with scorecards
- Measuring warehouse productivity metrics
- Calculating transportation cost per unit and route efficiency
- Identifying bottlenecks using throughput analysis
- Conducting ABC and XYZ analysis for inventory segmentation
- Reporting service level achievements and shortfalls
Module 5: Diagnostic Analytics – Understanding Why It Happened - Root cause analysis using data traces
- Conducting variance analysis for forecast vs actual
- Decomposing inventory obsolescence trends
- Analysing order delay patterns by node and carrier
- Identifying outliers and anomalies in shipment data
- Using scatter plots and correlation matrices to find drivers
- Analysing stockouts by SKU, location, and seasonality
- Diagnosing demand spikes and suppressed demand
- Mapping supply disruptions to historical events
- Linking customer complaints to fulfillment data
Module 6: Predictive Analytics – Forecasting What Will Happen - Introduction to forecasting models: moving averages, exponential smoothing
- Building single- and multi-step forecasts
- Choosing between time series and regression approaches
- Handling seasonality, trend, and cyclical components
- Validating models using holdout testing
- Calculating forecast accuracy: MAPE, RMSE, Bias
- Improving forecast inputs with leading indicators
- Blending statistical and judgemental forecasting
- Forecasting demand at multiple levels: SKU, product family, region
- Creating consensus forecasting processes
Module 7: Advanced Predictive Techniques for Complex Scenarios - Introducing machine learning concepts without coding
- Using regression trees for demand pattern detection
- Applying clustering to identify similar SKUs or customers
- Using anomaly detection for early risk alerts
- Building simple ensemble models for higher accuracy
- Forecasting under uncertainty with Monte Carlo simulations
- Scenario planning for supply shortages and demand surges
- Deriving confidence intervals for predictions
- Predicting lead time variability using historical distributions
- Anticipating supplier performance dips based on early warning signs
Module 8: Prescriptive Analytics – Deciding What to Do - Introduction to optimisation principles
- Setting objectives: minimise cost, maximise service, balance trade-offs
- Formulating constraints: capacity, budget, lead time
- Inventory optimisation: finding optimal reorder points and safety stock
- Transportation mode selection based on cost-service trade-offs
- Supplier allocation under risk and capacity limits
- Network design: evaluating warehouse location strategies
- Demand allocation across production sites
- Capacity planning using throughput ceilings
- Dynamic pricing and allocation based on predicted demand
Module 9: Analytics for Procurement and Supplier Management - Spend analytics and category segmentation
- Identifying cost-saving opportunities through data
- Supplier risk scoring using financial, delivery, and compliance data
- Tracking supplier lead time reliability and quality defects
- Calculating total cost of ownership (TCO)
- Benchmarking supplier performance across regions
- Analysing contract compliance and pricing deviations
- Forecasting raw material price trends
- Optimising procurement cycle times
- Building early warning systems for supplier disruptions
Module 10: Inventory and Demand Planning Analytics - Multi-echelon inventory analysis
- Calculating safety stock using service level targets
- Service level vs inventory cost trade-off curves
- Handling intermittent and lumpy demand
- Mean Absolute Deviation (MAD) for variability analysis
- Demand sensing using point-of-sale and syndicated data
- Collaborative planning with retail partners
- Managing new product introductions with limited data
- Phasing out products with declining demand
- Detecting demand corruption and order bias
Module 11: Logistics and Distribution Analytics - Route optimisation principles without complex software
- Evaluating last-mile delivery efficiency
- Analysing load utilisation and truck fill rates
- Comparing in-house vs outsourced fleet performance
- Network flow analysis for warehouse throughput
- Measuring dock-to-stock cycle times
- Reducing cross-docking delays with timing models
- Analysing warehouse pick paths and productivity
- Forecasting parcel volume and carrier capacity needs
- Reducing transportation carbon footprint with data
Module 12: Risk and Resilience Analytics - Mapping supply chain risk exposure by region and node
- Quantifying disruption impact using historical outage data
- Building supplier risk heat maps
- Monitoring geopolitical, weather, and port congestion data
- Calculating financial exposure to supply interruptions
- Developing contingency strategies with scenario models
- Measuring supply chain flexibility and adaptability
- Analyzing recovery time objectives (RTO) for critical nodes
- Building redundancy models for key components
- Assessing insurance adequacy using loss predictions
Module 13: Sustainability and ESG Analytics in Supply Chains - Measuring carbon footprint across transportation and warehousing
- Tracking emissions by mode, route, and supplier
- Analysing packaging waste and recyclability metrics
- Reporting on scope 3 emissions for compliance
- Setting and monitoring ESG KPIs
- Linking sustainability performance to cost and risk
- Identifying green procurement opportunities
- Creating supplier ESG scorecards
- Forecasting regulatory impact on sustainability requirements
- Aligning sustainability goals with operational efficiency
Module 14: Stakeholder Communication and Storytelling with Data - Translating technical analysis into business impact
- Building compelling narratives for leadership presentations
- Designing executive summaries with clear takeaways
- Using visuals to tell the story behind the numbers
- Anticipating and addressing stakeholder objections
- Aligning recommendations with strategic goals
- Creating actionable dashboards for non-technical users
- Documenting assumptions and limitations transparently
- Preparing for Q&A sessions on analytical findings
- Building trust through clarity and consistency
Module 15: Building and Leading Analytics Projects - Scoping an analytics project with clear deliverables
- Defining success criteria and measurable outcomes
- Securing buy-in from cross-functional teams
- Creating project timelines and milestone tracking
- Managing data access and permissions securely
- Running pilot tests and validating results
- Scaling successful pilots into operations
- Documenting processes for handover and maintenance
- Leveraging change management principles for adoption
- Gaining visibility and recognition for results
Module 16: Real-World Analytics Projects – Learn by Doing - Project 1: Reducing forecast error for a slow-moving SKU
- Project 2: Identifying excess inventory and recovery pathways
- Project 3: Diagnosing chronic late deliveries
- Project 4: Optimising safety stock levels across warehouses
- Project 5: Evaluating carrier performance and renegotiation potential
- Project 6: Building a supplier risk dashboard
- Project 7: Designing a sustainability reporting template
- Project 8: Creating a demand sensing prototype
- Project 9: Simulating the cost impact of a port closure
- Project 10: Developing a board-ready efficiency improvement proposal
Module 17: Integration with Enterprise Systems and Tools - Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- Understanding the role of analytics in modern supply chains
- Defining efficiency, resilience, and responsiveness metrics
- Identifying pain points where analytics deliver the highest ROI
- The evolution from descriptive to prescriptive analytics
- Data-driven decision making vs. intuition-based planning
- Common misconceptions and pitfalls in supply chain data
- Aligning analytics initiatives with business objectives
- Mapping the supply chain value chain for analytical leverage
- The difference between operational and strategic analytics
- Introduction to key performance indicators (KPIs) in logistics, procurement, and inventory
Module 2: Data Readiness and Quality Assurance - Assessing internal data sources and reliability
- Inventorying ERP, WMS, TMS, and POS system outputs
- Fixing common data issues: missing values, duplicates, and misalignment
- Standardising units, dates, and nomenclature across systems
- Building a clean, analytics-ready dataset
- Validating data accuracy through cross-system reconciliation
- Handling stale, incomplete, or inconsistent data
- Creating audit trails and version control for data integrity
- Building trusted baselines before modelling begins
- Documenting data lineage and governance protocols
Module 3: Core Analytical Frameworks and Methodologies - The 5-step supply chain analytics lifecycle
- Defining the problem and scoping the analytical approach
- Selecting the right methodology: descriptive, diagnostic, predictive, prescriptive
- Choosing between rule-based and statistical models
- Understanding assumption testing and model validation
- Introducing sensitivity and scenario analysis
- Building reusable templates for repeatable insights
- Creating logic trees for root-cause diagnosis
- Developing hypothesis-driven investigations
- Mapping decision flows to analytical requirements
Module 4: Descriptive Analytics – Measuring What Happened - Building comprehensive dashboards for visibility
- Selecting high-impact visualisations: time series, heat maps, Pareto charts
- Analysing order fulfilment rates and lead time performance
- Tracking inventory turnover and days of supply
- Evaluating supplier performance with scorecards
- Measuring warehouse productivity metrics
- Calculating transportation cost per unit and route efficiency
- Identifying bottlenecks using throughput analysis
- Conducting ABC and XYZ analysis for inventory segmentation
- Reporting service level achievements and shortfalls
Module 5: Diagnostic Analytics – Understanding Why It Happened - Root cause analysis using data traces
- Conducting variance analysis for forecast vs actual
- Decomposing inventory obsolescence trends
- Analysing order delay patterns by node and carrier
- Identifying outliers and anomalies in shipment data
- Using scatter plots and correlation matrices to find drivers
- Analysing stockouts by SKU, location, and seasonality
- Diagnosing demand spikes and suppressed demand
- Mapping supply disruptions to historical events
- Linking customer complaints to fulfillment data
Module 6: Predictive Analytics – Forecasting What Will Happen - Introduction to forecasting models: moving averages, exponential smoothing
- Building single- and multi-step forecasts
- Choosing between time series and regression approaches
- Handling seasonality, trend, and cyclical components
- Validating models using holdout testing
- Calculating forecast accuracy: MAPE, RMSE, Bias
- Improving forecast inputs with leading indicators
- Blending statistical and judgemental forecasting
- Forecasting demand at multiple levels: SKU, product family, region
- Creating consensus forecasting processes
Module 7: Advanced Predictive Techniques for Complex Scenarios - Introducing machine learning concepts without coding
- Using regression trees for demand pattern detection
- Applying clustering to identify similar SKUs or customers
- Using anomaly detection for early risk alerts
- Building simple ensemble models for higher accuracy
- Forecasting under uncertainty with Monte Carlo simulations
- Scenario planning for supply shortages and demand surges
- Deriving confidence intervals for predictions
- Predicting lead time variability using historical distributions
- Anticipating supplier performance dips based on early warning signs
Module 8: Prescriptive Analytics – Deciding What to Do - Introduction to optimisation principles
- Setting objectives: minimise cost, maximise service, balance trade-offs
- Formulating constraints: capacity, budget, lead time
- Inventory optimisation: finding optimal reorder points and safety stock
- Transportation mode selection based on cost-service trade-offs
- Supplier allocation under risk and capacity limits
- Network design: evaluating warehouse location strategies
- Demand allocation across production sites
- Capacity planning using throughput ceilings
- Dynamic pricing and allocation based on predicted demand
Module 9: Analytics for Procurement and Supplier Management - Spend analytics and category segmentation
- Identifying cost-saving opportunities through data
- Supplier risk scoring using financial, delivery, and compliance data
- Tracking supplier lead time reliability and quality defects
- Calculating total cost of ownership (TCO)
- Benchmarking supplier performance across regions
- Analysing contract compliance and pricing deviations
- Forecasting raw material price trends
- Optimising procurement cycle times
- Building early warning systems for supplier disruptions
Module 10: Inventory and Demand Planning Analytics - Multi-echelon inventory analysis
- Calculating safety stock using service level targets
- Service level vs inventory cost trade-off curves
- Handling intermittent and lumpy demand
- Mean Absolute Deviation (MAD) for variability analysis
- Demand sensing using point-of-sale and syndicated data
- Collaborative planning with retail partners
- Managing new product introductions with limited data
- Phasing out products with declining demand
- Detecting demand corruption and order bias
Module 11: Logistics and Distribution Analytics - Route optimisation principles without complex software
- Evaluating last-mile delivery efficiency
- Analysing load utilisation and truck fill rates
- Comparing in-house vs outsourced fleet performance
- Network flow analysis for warehouse throughput
- Measuring dock-to-stock cycle times
- Reducing cross-docking delays with timing models
- Analysing warehouse pick paths and productivity
- Forecasting parcel volume and carrier capacity needs
- Reducing transportation carbon footprint with data
Module 12: Risk and Resilience Analytics - Mapping supply chain risk exposure by region and node
- Quantifying disruption impact using historical outage data
- Building supplier risk heat maps
- Monitoring geopolitical, weather, and port congestion data
- Calculating financial exposure to supply interruptions
- Developing contingency strategies with scenario models
- Measuring supply chain flexibility and adaptability
- Analyzing recovery time objectives (RTO) for critical nodes
- Building redundancy models for key components
- Assessing insurance adequacy using loss predictions
Module 13: Sustainability and ESG Analytics in Supply Chains - Measuring carbon footprint across transportation and warehousing
- Tracking emissions by mode, route, and supplier
- Analysing packaging waste and recyclability metrics
- Reporting on scope 3 emissions for compliance
- Setting and monitoring ESG KPIs
- Linking sustainability performance to cost and risk
- Identifying green procurement opportunities
- Creating supplier ESG scorecards
- Forecasting regulatory impact on sustainability requirements
- Aligning sustainability goals with operational efficiency
Module 14: Stakeholder Communication and Storytelling with Data - Translating technical analysis into business impact
- Building compelling narratives for leadership presentations
- Designing executive summaries with clear takeaways
- Using visuals to tell the story behind the numbers
- Anticipating and addressing stakeholder objections
- Aligning recommendations with strategic goals
- Creating actionable dashboards for non-technical users
- Documenting assumptions and limitations transparently
- Preparing for Q&A sessions on analytical findings
- Building trust through clarity and consistency
Module 15: Building and Leading Analytics Projects - Scoping an analytics project with clear deliverables
- Defining success criteria and measurable outcomes
- Securing buy-in from cross-functional teams
- Creating project timelines and milestone tracking
- Managing data access and permissions securely
- Running pilot tests and validating results
- Scaling successful pilots into operations
- Documenting processes for handover and maintenance
- Leveraging change management principles for adoption
- Gaining visibility and recognition for results
Module 16: Real-World Analytics Projects – Learn by Doing - Project 1: Reducing forecast error for a slow-moving SKU
- Project 2: Identifying excess inventory and recovery pathways
- Project 3: Diagnosing chronic late deliveries
- Project 4: Optimising safety stock levels across warehouses
- Project 5: Evaluating carrier performance and renegotiation potential
- Project 6: Building a supplier risk dashboard
- Project 7: Designing a sustainability reporting template
- Project 8: Creating a demand sensing prototype
- Project 9: Simulating the cost impact of a port closure
- Project 10: Developing a board-ready efficiency improvement proposal
Module 17: Integration with Enterprise Systems and Tools - Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- The 5-step supply chain analytics lifecycle
- Defining the problem and scoping the analytical approach
- Selecting the right methodology: descriptive, diagnostic, predictive, prescriptive
- Choosing between rule-based and statistical models
- Understanding assumption testing and model validation
- Introducing sensitivity and scenario analysis
- Building reusable templates for repeatable insights
- Creating logic trees for root-cause diagnosis
- Developing hypothesis-driven investigations
- Mapping decision flows to analytical requirements
Module 4: Descriptive Analytics – Measuring What Happened - Building comprehensive dashboards for visibility
- Selecting high-impact visualisations: time series, heat maps, Pareto charts
- Analysing order fulfilment rates and lead time performance
- Tracking inventory turnover and days of supply
- Evaluating supplier performance with scorecards
- Measuring warehouse productivity metrics
- Calculating transportation cost per unit and route efficiency
- Identifying bottlenecks using throughput analysis
- Conducting ABC and XYZ analysis for inventory segmentation
- Reporting service level achievements and shortfalls
Module 5: Diagnostic Analytics – Understanding Why It Happened - Root cause analysis using data traces
- Conducting variance analysis for forecast vs actual
- Decomposing inventory obsolescence trends
- Analysing order delay patterns by node and carrier
- Identifying outliers and anomalies in shipment data
- Using scatter plots and correlation matrices to find drivers
- Analysing stockouts by SKU, location, and seasonality
- Diagnosing demand spikes and suppressed demand
- Mapping supply disruptions to historical events
- Linking customer complaints to fulfillment data
Module 6: Predictive Analytics – Forecasting What Will Happen - Introduction to forecasting models: moving averages, exponential smoothing
- Building single- and multi-step forecasts
- Choosing between time series and regression approaches
- Handling seasonality, trend, and cyclical components
- Validating models using holdout testing
- Calculating forecast accuracy: MAPE, RMSE, Bias
- Improving forecast inputs with leading indicators
- Blending statistical and judgemental forecasting
- Forecasting demand at multiple levels: SKU, product family, region
- Creating consensus forecasting processes
Module 7: Advanced Predictive Techniques for Complex Scenarios - Introducing machine learning concepts without coding
- Using regression trees for demand pattern detection
- Applying clustering to identify similar SKUs or customers
- Using anomaly detection for early risk alerts
- Building simple ensemble models for higher accuracy
- Forecasting under uncertainty with Monte Carlo simulations
- Scenario planning for supply shortages and demand surges
- Deriving confidence intervals for predictions
- Predicting lead time variability using historical distributions
- Anticipating supplier performance dips based on early warning signs
Module 8: Prescriptive Analytics – Deciding What to Do - Introduction to optimisation principles
- Setting objectives: minimise cost, maximise service, balance trade-offs
- Formulating constraints: capacity, budget, lead time
- Inventory optimisation: finding optimal reorder points and safety stock
- Transportation mode selection based on cost-service trade-offs
- Supplier allocation under risk and capacity limits
- Network design: evaluating warehouse location strategies
- Demand allocation across production sites
- Capacity planning using throughput ceilings
- Dynamic pricing and allocation based on predicted demand
Module 9: Analytics for Procurement and Supplier Management - Spend analytics and category segmentation
- Identifying cost-saving opportunities through data
- Supplier risk scoring using financial, delivery, and compliance data
- Tracking supplier lead time reliability and quality defects
- Calculating total cost of ownership (TCO)
- Benchmarking supplier performance across regions
- Analysing contract compliance and pricing deviations
- Forecasting raw material price trends
- Optimising procurement cycle times
- Building early warning systems for supplier disruptions
Module 10: Inventory and Demand Planning Analytics - Multi-echelon inventory analysis
- Calculating safety stock using service level targets
- Service level vs inventory cost trade-off curves
- Handling intermittent and lumpy demand
- Mean Absolute Deviation (MAD) for variability analysis
- Demand sensing using point-of-sale and syndicated data
- Collaborative planning with retail partners
- Managing new product introductions with limited data
- Phasing out products with declining demand
- Detecting demand corruption and order bias
Module 11: Logistics and Distribution Analytics - Route optimisation principles without complex software
- Evaluating last-mile delivery efficiency
- Analysing load utilisation and truck fill rates
- Comparing in-house vs outsourced fleet performance
- Network flow analysis for warehouse throughput
- Measuring dock-to-stock cycle times
- Reducing cross-docking delays with timing models
- Analysing warehouse pick paths and productivity
- Forecasting parcel volume and carrier capacity needs
- Reducing transportation carbon footprint with data
Module 12: Risk and Resilience Analytics - Mapping supply chain risk exposure by region and node
- Quantifying disruption impact using historical outage data
- Building supplier risk heat maps
- Monitoring geopolitical, weather, and port congestion data
- Calculating financial exposure to supply interruptions
- Developing contingency strategies with scenario models
- Measuring supply chain flexibility and adaptability
- Analyzing recovery time objectives (RTO) for critical nodes
- Building redundancy models for key components
- Assessing insurance adequacy using loss predictions
Module 13: Sustainability and ESG Analytics in Supply Chains - Measuring carbon footprint across transportation and warehousing
- Tracking emissions by mode, route, and supplier
- Analysing packaging waste and recyclability metrics
- Reporting on scope 3 emissions for compliance
- Setting and monitoring ESG KPIs
- Linking sustainability performance to cost and risk
- Identifying green procurement opportunities
- Creating supplier ESG scorecards
- Forecasting regulatory impact on sustainability requirements
- Aligning sustainability goals with operational efficiency
Module 14: Stakeholder Communication and Storytelling with Data - Translating technical analysis into business impact
- Building compelling narratives for leadership presentations
- Designing executive summaries with clear takeaways
- Using visuals to tell the story behind the numbers
- Anticipating and addressing stakeholder objections
- Aligning recommendations with strategic goals
- Creating actionable dashboards for non-technical users
- Documenting assumptions and limitations transparently
- Preparing for Q&A sessions on analytical findings
- Building trust through clarity and consistency
Module 15: Building and Leading Analytics Projects - Scoping an analytics project with clear deliverables
- Defining success criteria and measurable outcomes
- Securing buy-in from cross-functional teams
- Creating project timelines and milestone tracking
- Managing data access and permissions securely
- Running pilot tests and validating results
- Scaling successful pilots into operations
- Documenting processes for handover and maintenance
- Leveraging change management principles for adoption
- Gaining visibility and recognition for results
Module 16: Real-World Analytics Projects – Learn by Doing - Project 1: Reducing forecast error for a slow-moving SKU
- Project 2: Identifying excess inventory and recovery pathways
- Project 3: Diagnosing chronic late deliveries
- Project 4: Optimising safety stock levels across warehouses
- Project 5: Evaluating carrier performance and renegotiation potential
- Project 6: Building a supplier risk dashboard
- Project 7: Designing a sustainability reporting template
- Project 8: Creating a demand sensing prototype
- Project 9: Simulating the cost impact of a port closure
- Project 10: Developing a board-ready efficiency improvement proposal
Module 17: Integration with Enterprise Systems and Tools - Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- Root cause analysis using data traces
- Conducting variance analysis for forecast vs actual
- Decomposing inventory obsolescence trends
- Analysing order delay patterns by node and carrier
- Identifying outliers and anomalies in shipment data
- Using scatter plots and correlation matrices to find drivers
- Analysing stockouts by SKU, location, and seasonality
- Diagnosing demand spikes and suppressed demand
- Mapping supply disruptions to historical events
- Linking customer complaints to fulfillment data
Module 6: Predictive Analytics – Forecasting What Will Happen - Introduction to forecasting models: moving averages, exponential smoothing
- Building single- and multi-step forecasts
- Choosing between time series and regression approaches
- Handling seasonality, trend, and cyclical components
- Validating models using holdout testing
- Calculating forecast accuracy: MAPE, RMSE, Bias
- Improving forecast inputs with leading indicators
- Blending statistical and judgemental forecasting
- Forecasting demand at multiple levels: SKU, product family, region
- Creating consensus forecasting processes
Module 7: Advanced Predictive Techniques for Complex Scenarios - Introducing machine learning concepts without coding
- Using regression trees for demand pattern detection
- Applying clustering to identify similar SKUs or customers
- Using anomaly detection for early risk alerts
- Building simple ensemble models for higher accuracy
- Forecasting under uncertainty with Monte Carlo simulations
- Scenario planning for supply shortages and demand surges
- Deriving confidence intervals for predictions
- Predicting lead time variability using historical distributions
- Anticipating supplier performance dips based on early warning signs
Module 8: Prescriptive Analytics – Deciding What to Do - Introduction to optimisation principles
- Setting objectives: minimise cost, maximise service, balance trade-offs
- Formulating constraints: capacity, budget, lead time
- Inventory optimisation: finding optimal reorder points and safety stock
- Transportation mode selection based on cost-service trade-offs
- Supplier allocation under risk and capacity limits
- Network design: evaluating warehouse location strategies
- Demand allocation across production sites
- Capacity planning using throughput ceilings
- Dynamic pricing and allocation based on predicted demand
Module 9: Analytics for Procurement and Supplier Management - Spend analytics and category segmentation
- Identifying cost-saving opportunities through data
- Supplier risk scoring using financial, delivery, and compliance data
- Tracking supplier lead time reliability and quality defects
- Calculating total cost of ownership (TCO)
- Benchmarking supplier performance across regions
- Analysing contract compliance and pricing deviations
- Forecasting raw material price trends
- Optimising procurement cycle times
- Building early warning systems for supplier disruptions
Module 10: Inventory and Demand Planning Analytics - Multi-echelon inventory analysis
- Calculating safety stock using service level targets
- Service level vs inventory cost trade-off curves
- Handling intermittent and lumpy demand
- Mean Absolute Deviation (MAD) for variability analysis
- Demand sensing using point-of-sale and syndicated data
- Collaborative planning with retail partners
- Managing new product introductions with limited data
- Phasing out products with declining demand
- Detecting demand corruption and order bias
Module 11: Logistics and Distribution Analytics - Route optimisation principles without complex software
- Evaluating last-mile delivery efficiency
- Analysing load utilisation and truck fill rates
- Comparing in-house vs outsourced fleet performance
- Network flow analysis for warehouse throughput
- Measuring dock-to-stock cycle times
- Reducing cross-docking delays with timing models
- Analysing warehouse pick paths and productivity
- Forecasting parcel volume and carrier capacity needs
- Reducing transportation carbon footprint with data
Module 12: Risk and Resilience Analytics - Mapping supply chain risk exposure by region and node
- Quantifying disruption impact using historical outage data
- Building supplier risk heat maps
- Monitoring geopolitical, weather, and port congestion data
- Calculating financial exposure to supply interruptions
- Developing contingency strategies with scenario models
- Measuring supply chain flexibility and adaptability
- Analyzing recovery time objectives (RTO) for critical nodes
- Building redundancy models for key components
- Assessing insurance adequacy using loss predictions
Module 13: Sustainability and ESG Analytics in Supply Chains - Measuring carbon footprint across transportation and warehousing
- Tracking emissions by mode, route, and supplier
- Analysing packaging waste and recyclability metrics
- Reporting on scope 3 emissions for compliance
- Setting and monitoring ESG KPIs
- Linking sustainability performance to cost and risk
- Identifying green procurement opportunities
- Creating supplier ESG scorecards
- Forecasting regulatory impact on sustainability requirements
- Aligning sustainability goals with operational efficiency
Module 14: Stakeholder Communication and Storytelling with Data - Translating technical analysis into business impact
- Building compelling narratives for leadership presentations
- Designing executive summaries with clear takeaways
- Using visuals to tell the story behind the numbers
- Anticipating and addressing stakeholder objections
- Aligning recommendations with strategic goals
- Creating actionable dashboards for non-technical users
- Documenting assumptions and limitations transparently
- Preparing for Q&A sessions on analytical findings
- Building trust through clarity and consistency
Module 15: Building and Leading Analytics Projects - Scoping an analytics project with clear deliverables
- Defining success criteria and measurable outcomes
- Securing buy-in from cross-functional teams
- Creating project timelines and milestone tracking
- Managing data access and permissions securely
- Running pilot tests and validating results
- Scaling successful pilots into operations
- Documenting processes for handover and maintenance
- Leveraging change management principles for adoption
- Gaining visibility and recognition for results
Module 16: Real-World Analytics Projects – Learn by Doing - Project 1: Reducing forecast error for a slow-moving SKU
- Project 2: Identifying excess inventory and recovery pathways
- Project 3: Diagnosing chronic late deliveries
- Project 4: Optimising safety stock levels across warehouses
- Project 5: Evaluating carrier performance and renegotiation potential
- Project 6: Building a supplier risk dashboard
- Project 7: Designing a sustainability reporting template
- Project 8: Creating a demand sensing prototype
- Project 9: Simulating the cost impact of a port closure
- Project 10: Developing a board-ready efficiency improvement proposal
Module 17: Integration with Enterprise Systems and Tools - Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- Introducing machine learning concepts without coding
- Using regression trees for demand pattern detection
- Applying clustering to identify similar SKUs or customers
- Using anomaly detection for early risk alerts
- Building simple ensemble models for higher accuracy
- Forecasting under uncertainty with Monte Carlo simulations
- Scenario planning for supply shortages and demand surges
- Deriving confidence intervals for predictions
- Predicting lead time variability using historical distributions
- Anticipating supplier performance dips based on early warning signs
Module 8: Prescriptive Analytics – Deciding What to Do - Introduction to optimisation principles
- Setting objectives: minimise cost, maximise service, balance trade-offs
- Formulating constraints: capacity, budget, lead time
- Inventory optimisation: finding optimal reorder points and safety stock
- Transportation mode selection based on cost-service trade-offs
- Supplier allocation under risk and capacity limits
- Network design: evaluating warehouse location strategies
- Demand allocation across production sites
- Capacity planning using throughput ceilings
- Dynamic pricing and allocation based on predicted demand
Module 9: Analytics for Procurement and Supplier Management - Spend analytics and category segmentation
- Identifying cost-saving opportunities through data
- Supplier risk scoring using financial, delivery, and compliance data
- Tracking supplier lead time reliability and quality defects
- Calculating total cost of ownership (TCO)
- Benchmarking supplier performance across regions
- Analysing contract compliance and pricing deviations
- Forecasting raw material price trends
- Optimising procurement cycle times
- Building early warning systems for supplier disruptions
Module 10: Inventory and Demand Planning Analytics - Multi-echelon inventory analysis
- Calculating safety stock using service level targets
- Service level vs inventory cost trade-off curves
- Handling intermittent and lumpy demand
- Mean Absolute Deviation (MAD) for variability analysis
- Demand sensing using point-of-sale and syndicated data
- Collaborative planning with retail partners
- Managing new product introductions with limited data
- Phasing out products with declining demand
- Detecting demand corruption and order bias
Module 11: Logistics and Distribution Analytics - Route optimisation principles without complex software
- Evaluating last-mile delivery efficiency
- Analysing load utilisation and truck fill rates
- Comparing in-house vs outsourced fleet performance
- Network flow analysis for warehouse throughput
- Measuring dock-to-stock cycle times
- Reducing cross-docking delays with timing models
- Analysing warehouse pick paths and productivity
- Forecasting parcel volume and carrier capacity needs
- Reducing transportation carbon footprint with data
Module 12: Risk and Resilience Analytics - Mapping supply chain risk exposure by region and node
- Quantifying disruption impact using historical outage data
- Building supplier risk heat maps
- Monitoring geopolitical, weather, and port congestion data
- Calculating financial exposure to supply interruptions
- Developing contingency strategies with scenario models
- Measuring supply chain flexibility and adaptability
- Analyzing recovery time objectives (RTO) for critical nodes
- Building redundancy models for key components
- Assessing insurance adequacy using loss predictions
Module 13: Sustainability and ESG Analytics in Supply Chains - Measuring carbon footprint across transportation and warehousing
- Tracking emissions by mode, route, and supplier
- Analysing packaging waste and recyclability metrics
- Reporting on scope 3 emissions for compliance
- Setting and monitoring ESG KPIs
- Linking sustainability performance to cost and risk
- Identifying green procurement opportunities
- Creating supplier ESG scorecards
- Forecasting regulatory impact on sustainability requirements
- Aligning sustainability goals with operational efficiency
Module 14: Stakeholder Communication and Storytelling with Data - Translating technical analysis into business impact
- Building compelling narratives for leadership presentations
- Designing executive summaries with clear takeaways
- Using visuals to tell the story behind the numbers
- Anticipating and addressing stakeholder objections
- Aligning recommendations with strategic goals
- Creating actionable dashboards for non-technical users
- Documenting assumptions and limitations transparently
- Preparing for Q&A sessions on analytical findings
- Building trust through clarity and consistency
Module 15: Building and Leading Analytics Projects - Scoping an analytics project with clear deliverables
- Defining success criteria and measurable outcomes
- Securing buy-in from cross-functional teams
- Creating project timelines and milestone tracking
- Managing data access and permissions securely
- Running pilot tests and validating results
- Scaling successful pilots into operations
- Documenting processes for handover and maintenance
- Leveraging change management principles for adoption
- Gaining visibility and recognition for results
Module 16: Real-World Analytics Projects – Learn by Doing - Project 1: Reducing forecast error for a slow-moving SKU
- Project 2: Identifying excess inventory and recovery pathways
- Project 3: Diagnosing chronic late deliveries
- Project 4: Optimising safety stock levels across warehouses
- Project 5: Evaluating carrier performance and renegotiation potential
- Project 6: Building a supplier risk dashboard
- Project 7: Designing a sustainability reporting template
- Project 8: Creating a demand sensing prototype
- Project 9: Simulating the cost impact of a port closure
- Project 10: Developing a board-ready efficiency improvement proposal
Module 17: Integration with Enterprise Systems and Tools - Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- Spend analytics and category segmentation
- Identifying cost-saving opportunities through data
- Supplier risk scoring using financial, delivery, and compliance data
- Tracking supplier lead time reliability and quality defects
- Calculating total cost of ownership (TCO)
- Benchmarking supplier performance across regions
- Analysing contract compliance and pricing deviations
- Forecasting raw material price trends
- Optimising procurement cycle times
- Building early warning systems for supplier disruptions
Module 10: Inventory and Demand Planning Analytics - Multi-echelon inventory analysis
- Calculating safety stock using service level targets
- Service level vs inventory cost trade-off curves
- Handling intermittent and lumpy demand
- Mean Absolute Deviation (MAD) for variability analysis
- Demand sensing using point-of-sale and syndicated data
- Collaborative planning with retail partners
- Managing new product introductions with limited data
- Phasing out products with declining demand
- Detecting demand corruption and order bias
Module 11: Logistics and Distribution Analytics - Route optimisation principles without complex software
- Evaluating last-mile delivery efficiency
- Analysing load utilisation and truck fill rates
- Comparing in-house vs outsourced fleet performance
- Network flow analysis for warehouse throughput
- Measuring dock-to-stock cycle times
- Reducing cross-docking delays with timing models
- Analysing warehouse pick paths and productivity
- Forecasting parcel volume and carrier capacity needs
- Reducing transportation carbon footprint with data
Module 12: Risk and Resilience Analytics - Mapping supply chain risk exposure by region and node
- Quantifying disruption impact using historical outage data
- Building supplier risk heat maps
- Monitoring geopolitical, weather, and port congestion data
- Calculating financial exposure to supply interruptions
- Developing contingency strategies with scenario models
- Measuring supply chain flexibility and adaptability
- Analyzing recovery time objectives (RTO) for critical nodes
- Building redundancy models for key components
- Assessing insurance adequacy using loss predictions
Module 13: Sustainability and ESG Analytics in Supply Chains - Measuring carbon footprint across transportation and warehousing
- Tracking emissions by mode, route, and supplier
- Analysing packaging waste and recyclability metrics
- Reporting on scope 3 emissions for compliance
- Setting and monitoring ESG KPIs
- Linking sustainability performance to cost and risk
- Identifying green procurement opportunities
- Creating supplier ESG scorecards
- Forecasting regulatory impact on sustainability requirements
- Aligning sustainability goals with operational efficiency
Module 14: Stakeholder Communication and Storytelling with Data - Translating technical analysis into business impact
- Building compelling narratives for leadership presentations
- Designing executive summaries with clear takeaways
- Using visuals to tell the story behind the numbers
- Anticipating and addressing stakeholder objections
- Aligning recommendations with strategic goals
- Creating actionable dashboards for non-technical users
- Documenting assumptions and limitations transparently
- Preparing for Q&A sessions on analytical findings
- Building trust through clarity and consistency
Module 15: Building and Leading Analytics Projects - Scoping an analytics project with clear deliverables
- Defining success criteria and measurable outcomes
- Securing buy-in from cross-functional teams
- Creating project timelines and milestone tracking
- Managing data access and permissions securely
- Running pilot tests and validating results
- Scaling successful pilots into operations
- Documenting processes for handover and maintenance
- Leveraging change management principles for adoption
- Gaining visibility and recognition for results
Module 16: Real-World Analytics Projects – Learn by Doing - Project 1: Reducing forecast error for a slow-moving SKU
- Project 2: Identifying excess inventory and recovery pathways
- Project 3: Diagnosing chronic late deliveries
- Project 4: Optimising safety stock levels across warehouses
- Project 5: Evaluating carrier performance and renegotiation potential
- Project 6: Building a supplier risk dashboard
- Project 7: Designing a sustainability reporting template
- Project 8: Creating a demand sensing prototype
- Project 9: Simulating the cost impact of a port closure
- Project 10: Developing a board-ready efficiency improvement proposal
Module 17: Integration with Enterprise Systems and Tools - Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- Route optimisation principles without complex software
- Evaluating last-mile delivery efficiency
- Analysing load utilisation and truck fill rates
- Comparing in-house vs outsourced fleet performance
- Network flow analysis for warehouse throughput
- Measuring dock-to-stock cycle times
- Reducing cross-docking delays with timing models
- Analysing warehouse pick paths and productivity
- Forecasting parcel volume and carrier capacity needs
- Reducing transportation carbon footprint with data
Module 12: Risk and Resilience Analytics - Mapping supply chain risk exposure by region and node
- Quantifying disruption impact using historical outage data
- Building supplier risk heat maps
- Monitoring geopolitical, weather, and port congestion data
- Calculating financial exposure to supply interruptions
- Developing contingency strategies with scenario models
- Measuring supply chain flexibility and adaptability
- Analyzing recovery time objectives (RTO) for critical nodes
- Building redundancy models for key components
- Assessing insurance adequacy using loss predictions
Module 13: Sustainability and ESG Analytics in Supply Chains - Measuring carbon footprint across transportation and warehousing
- Tracking emissions by mode, route, and supplier
- Analysing packaging waste and recyclability metrics
- Reporting on scope 3 emissions for compliance
- Setting and monitoring ESG KPIs
- Linking sustainability performance to cost and risk
- Identifying green procurement opportunities
- Creating supplier ESG scorecards
- Forecasting regulatory impact on sustainability requirements
- Aligning sustainability goals with operational efficiency
Module 14: Stakeholder Communication and Storytelling with Data - Translating technical analysis into business impact
- Building compelling narratives for leadership presentations
- Designing executive summaries with clear takeaways
- Using visuals to tell the story behind the numbers
- Anticipating and addressing stakeholder objections
- Aligning recommendations with strategic goals
- Creating actionable dashboards for non-technical users
- Documenting assumptions and limitations transparently
- Preparing for Q&A sessions on analytical findings
- Building trust through clarity and consistency
Module 15: Building and Leading Analytics Projects - Scoping an analytics project with clear deliverables
- Defining success criteria and measurable outcomes
- Securing buy-in from cross-functional teams
- Creating project timelines and milestone tracking
- Managing data access and permissions securely
- Running pilot tests and validating results
- Scaling successful pilots into operations
- Documenting processes for handover and maintenance
- Leveraging change management principles for adoption
- Gaining visibility and recognition for results
Module 16: Real-World Analytics Projects – Learn by Doing - Project 1: Reducing forecast error for a slow-moving SKU
- Project 2: Identifying excess inventory and recovery pathways
- Project 3: Diagnosing chronic late deliveries
- Project 4: Optimising safety stock levels across warehouses
- Project 5: Evaluating carrier performance and renegotiation potential
- Project 6: Building a supplier risk dashboard
- Project 7: Designing a sustainability reporting template
- Project 8: Creating a demand sensing prototype
- Project 9: Simulating the cost impact of a port closure
- Project 10: Developing a board-ready efficiency improvement proposal
Module 17: Integration with Enterprise Systems and Tools - Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- Measuring carbon footprint across transportation and warehousing
- Tracking emissions by mode, route, and supplier
- Analysing packaging waste and recyclability metrics
- Reporting on scope 3 emissions for compliance
- Setting and monitoring ESG KPIs
- Linking sustainability performance to cost and risk
- Identifying green procurement opportunities
- Creating supplier ESG scorecards
- Forecasting regulatory impact on sustainability requirements
- Aligning sustainability goals with operational efficiency
Module 14: Stakeholder Communication and Storytelling with Data - Translating technical analysis into business impact
- Building compelling narratives for leadership presentations
- Designing executive summaries with clear takeaways
- Using visuals to tell the story behind the numbers
- Anticipating and addressing stakeholder objections
- Aligning recommendations with strategic goals
- Creating actionable dashboards for non-technical users
- Documenting assumptions and limitations transparently
- Preparing for Q&A sessions on analytical findings
- Building trust through clarity and consistency
Module 15: Building and Leading Analytics Projects - Scoping an analytics project with clear deliverables
- Defining success criteria and measurable outcomes
- Securing buy-in from cross-functional teams
- Creating project timelines and milestone tracking
- Managing data access and permissions securely
- Running pilot tests and validating results
- Scaling successful pilots into operations
- Documenting processes for handover and maintenance
- Leveraging change management principles for adoption
- Gaining visibility and recognition for results
Module 16: Real-World Analytics Projects – Learn by Doing - Project 1: Reducing forecast error for a slow-moving SKU
- Project 2: Identifying excess inventory and recovery pathways
- Project 3: Diagnosing chronic late deliveries
- Project 4: Optimising safety stock levels across warehouses
- Project 5: Evaluating carrier performance and renegotiation potential
- Project 6: Building a supplier risk dashboard
- Project 7: Designing a sustainability reporting template
- Project 8: Creating a demand sensing prototype
- Project 9: Simulating the cost impact of a port closure
- Project 10: Developing a board-ready efficiency improvement proposal
Module 17: Integration with Enterprise Systems and Tools - Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- Scoping an analytics project with clear deliverables
- Defining success criteria and measurable outcomes
- Securing buy-in from cross-functional teams
- Creating project timelines and milestone tracking
- Managing data access and permissions securely
- Running pilot tests and validating results
- Scaling successful pilots into operations
- Documenting processes for handover and maintenance
- Leveraging change management principles for adoption
- Gaining visibility and recognition for results
Module 16: Real-World Analytics Projects – Learn by Doing - Project 1: Reducing forecast error for a slow-moving SKU
- Project 2: Identifying excess inventory and recovery pathways
- Project 3: Diagnosing chronic late deliveries
- Project 4: Optimising safety stock levels across warehouses
- Project 5: Evaluating carrier performance and renegotiation potential
- Project 6: Building a supplier risk dashboard
- Project 7: Designing a sustainability reporting template
- Project 8: Creating a demand sensing prototype
- Project 9: Simulating the cost impact of a port closure
- Project 10: Developing a board-ready efficiency improvement proposal
Module 17: Integration with Enterprise Systems and Tools - Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- Connecting analytics outputs to SAP, Oracle, and NetSuite
- Exporting and importing data using CSV and APIs
- Automating data flows with scheduler tools
- Using Excel and Google Sheets effectively for analytics
- Leveraging Power BI and Tableau for visual reporting
- Validation checks for system-to-system data transfers
- Maintaining data integrity during integration
- Creating self-updating dashboards
- Setting up alerts and thresholds for operational triggers
- Ensuring compliance with data governance policies
Module 18: Career Advancement and Professional Growth - Positioning yourself as a data-driven leader
- Building a portfolio of analytical achievements
- Updating your LinkedIn and resume with analytics impact
- Communicating ROI from your projects in interviews
- Preparing for supply chain analytics certification exams
- Networking with analytics professionals
- Transitioning to roles in analytics, planning, or consulting
- Negotiating higher compensation based on demonstrated value
- Leading cross-functional improvement initiatives
- Staying current with emerging trends and methodologies
Module 19: Certification, Final Assessment, and Next Steps - Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence
- Reviewing all core concepts and frameworks
- Completing the final case study: end-to-end analytics project
- Submitting your board-ready proposal for assessment
- Receiving structured feedback on your work
- Accessing your Certificate of Completion from The Art of Service
- Sharing your credential on LinkedIn and professional platforms
- Joining the alumni network for ongoing learning
- Accessing updated templates and case studies
- Tracking your progress with the built-in learning dashboard
- Planning your next career move with confidence